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Since its inception, the field of unbiased learning to rank (ULTR) hasremained very active and has seen several impactful advancements in recentyears. This tutorial provides both an introduction to the core concepts of thefield and an overview of recent advancements in its foundations along withseveral applications of its methods. The tutorial is divided into four parts:Firstly, we give an overview of the different forms of bias that can beaddressed with ULTR methods. Secondly, we present a comprehensive discussion ofthe latest estimation techniques in the ULTR field. Thirdly, we surveypublished results of ULTR in real-world applications. Fourthly, we discuss theconnection between ULTR and fairness in ranking. We end by briefly reflectingon the future of ULTR research and its applications. This tutorial is intendedto benefit both researchers and industry practitioners who are interested indeveloping new ULTR solutions or utilizing them in real-world applications.

Recent Advances in the Foundations and Applications of Unbiased Learning to Rank